Evolution of a user interface based on learned idiosyncrasies and collected data of a user

ABSTRACT

A user interface evolves based on learned idiosyncrasies and collected data of a user. Learned idiosyncrasies and collected data of the user can be stored in a knowledge base. Information from the surrounding environment of the user can be obtained during learning of idiosyncrasies or collection of data. Thought-based statements can be generated based at least in part on the knowledge base and the information from the environment surrounding the user during learning of idiosyncrasies or collection of data. The thought-based statements serve to invoke or respond to subsequent actions of the user. The user interface can be presented so as to allow for interaction with the user based at least in part on the thought-based statements. Furthermore, personality nuances of the user interface can be developed that affect the interaction between the user and the user interface.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to user interfaces. Morespecifically, the present invention relates to providing an intelligentuser interface that evolves based on learned idiosyncrasies andcollected data of a user.

2. Description of the Related Art

A user interface is an aggregate of means by which people—users—interactwith a system such as a particular machine, device, computer program, orother complex tool. The user interface provides means of input andoutput. The input means allow the user to manipulate the system, whilethe output means allow the system to indicate the effects of the usermanipulation. The design of a user interface affects the amount ofeffort a user must expend to provide input for the system and tointerpret output of the system. Usability is the degree to which thedesign of a particular user interface takes into account the humanpsychology and behavioral characteristics of the users, and makes theprocess of using the system effective, efficient and satisfying.

Current user interfaces are, at best, minimally personalized. Generally,these user interfaces are available with factory-set defaults that areselected with the general population or another large user group inmind. Users may be provided with the option of changing certainpreferences; however any preference changes will be limited to apredefined list thereof. Furthermore, any customized behavior of theseuser interfaces must be specifically programmed by the user orotherwise. Given these and other limitations with current userinterfaces, what is needed is a user interface that evolves in variousaspects during use based on characteristics, habits, and other dataassociated with a user.

SUMMARY OF THE CLAIMED INVENTION

Embodiments of the present invention allow an intelligent user interfaceto be provided that evolves based on learned idiosyncrasies andcollected data of a user.

In a claimed embodiment, a method is set forth for providing a userinterface that evolves based on learned idiosyncrasies and collecteddata of a user. Learned idiosyncrasies and collected data of the userare stored in a knowledge base. Instructions stored in memory areexecuted to obtain information from the surrounding environment of theuser during learning of idiosyncrasies or collection of data.Instructions stored in memory are executed to generate thought-basedstatements based at least in part on the knowledge base and theinformation from the environment surrounding the user during learning ofidiosyncrasies or collection of data. The thought-based statements serveto invoke or respond to subsequent actions of the user. Instructionsstored in memory are executed to present the user interface and to allowfor interaction with the user based at least in part on thethought-based statements.

Another claimed embodiment sets forth a system for providing a userinterface that evolves based on learned idiosyncrasies and collecteddata of a user. The system includes a knowledge base, a sensory engine,a thought engine, and an interaction engine, all of which are stored inmemory. The knowledge base is configured to store learned idiosyncrasiesand collected data of the user. The sensory engine is executable toobtain information from the surrounding environment of the user duringlearning of idiosyncrasies or collection of data. The thought engine isexecutable to generate thought-based statements based at least in parton the knowledge base and the information from the environmentsurrounding the user during learning of idiosyncrasies or collection ofdata. The thought-based statements serve to invoke or respond tosubsequent actions of the user. The interaction engine is executable topresent the user interface and to allow for interaction with the userbased at least in part on the thought-based statements.

A computer-readable storage medium is set forth in yet another claimedembodiment. A program is embodied on the computer-readable storagemedium, which is executable by a processor to perform a method forproviding a user interface that evolves based on learned idiosyncrasiesand collected data of a user. The method includes storing learnedidiosyncrasies and collected data of the user in a knowledge base,obtaining information from the surrounding environment of the userduring learning of idiosyncrasies or collection of data, generatingthought-based statements based at least in part on the knowledge baseand the information from the environment surrounding the user duringlearning of idiosyncrasies or collection of data, and presenting theuser interface and to allow for interaction with the user based at leastin part on the thought-based statements. The thought-based statementsserve to invoke or respond to subsequent actions of the user

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 illustrates an environment for providing an intelligent userinterface that evolves based on learned idiosyncrasies and collecteddata of a user.

FIG. 2 is a block diagram of an exemplary intelligent user interfacesystem that may be invoked in the environment illustrated in FIG. 1.

FIG. 3 is a block diagram of an exemplary sensory engine that may beincluded in the intelligent user interface system.

FIG. 4 is a block diagram of an exemplary thought engine that may beincluded in the intelligent user interface system.

FIG. 5 is a block diagram of an exemplary interaction engine that may beincluded in the intelligent user interface system.

FIG. 6 is a collection of exemplary avatars that may be included in theintelligent user interface.

FIG. 7 is a block diagram of an exemplary personality engine that may beincluded in the intelligent user interface system.

FIG. 8 is a flowchart illustrating an exemplary method for providing anintelligent user interface that evolves based on learned idiosyncrasiesand collected data of a user.

FIG. 9 is a block diagram illustrating an exemplary device that may beused to implement an embodiment of the present invention.

DETAILED DESCRIPTION

Embodiments of the presently disclosed invention allow an intelligentuser interface to be provided that evolves based on learnedidiosyncrasies and collected data of a user. As the user interacts withthe intelligent user interface, idiosyncrasies of the user such ashabits and rituals will be learned. Additionally, data associated withthe user will be collected from local and remote sources. Examples oflocal data include a catalog of user media or services available to asystem presenting the user interface. Examples of remote data include anindex of information from third-party accounts associated with the useror textual communication by the user. Further information can beobtained through interactive dialog with the user in which the userexplicitly or implicitly provides the information thought verbal input.

The sum of obtained information associated with the user—both local andremote—can be stored in a regularly-updated knowledge base and be usedto generate thought-based statements. The thought-based statements serveto invoke or respond to subsequent actions of the user. Though thisiterative process of “getting to know” the user, the user interfaceevolves to better satisfy the wants and needs of the user.

FIG. 1 illustrates an environment 100 for providing an intelligent userinterface that evolves based on learned idiosyncrasies and collecteddata of a user. As depicted, the environment 100 includes a user device105 in communication with a network 110. Remote data sources 115 and anoptional server 120 are also in communication with the network 110. Thenetwork 110 facilitates communication between the user device 105, theremote data sources 115, the server 120, and other devicescommunicatively coupled with the network 110. The user device 105, theremote data sources 115, and the server 120 include the requisitenetwork interfaces, memory, and processing components as may be requiredto interact with one another via the network 110. User environment 125includes an area that surrounds the user device 105 and a user thereof.Such an area could, for example, be a living room.

Both the user device 105 and the server 120 are shown as including anintelligent user interface system 130, however, the user interfacesystem 130 may reside entirely in one device or may be distributedacross two or more networked devices. The intelligent user interfacesystem 130 is described in further detail in connection with FIG. 2.Environment 100 may include many devices such as the user device 105 andthe server 120 in communication via the network 110.

The user device 105 can facilitate presentation of an intelligent userinterface by way of the intelligent user interface system 130. While theuser device 105 is depicted in FIG. 1 as housing the intelligent userinterface system 130, the user device 105 may access via the network 110an instance of the intelligent user interface 130 residing on a remotecomputer such as the server 120. Similarly, the user device 105 mayexecute certain components of the intelligent user interface system 130locally and access other components remotely via the network 110.

The user device 105 may include any portable consumer electronics devicesuch as a smart phone, portable media playback device, or gaming device.Examples of the user device 105 include portable gaming devices such asa PSP™ and PSP Go from Sony Computer Entertainment Inc. The user device105 may also include car stereos, e-book readers, and portablecomputers. The user device 105 may include one or more integrated outputdevices for presenting media or may also allow for an external couplingto the same (e.g., a display and speakers).

The user device 105 may also include any consumer electronics notspecifically designed for portability. Examples of the user device 105include a home entertainment system such as the PlayStation®3 availablefrom Sony Computer Entertainment Inc. or more limited game hardwareplatforms of a different albeit inferior manufacture than those offeredby Sony Computer Entertainment. Further examples of consumer electronicsdevices include various home theater components such as a DigitalVersatile Disc (DVD) player, a Blu-Ray Disc player, a Digital VideoRecorder, set-top cable boxes, and personal computers. The user device105 may include one or more integrated output devices for presentingmedia or be coupled to the same.

The remote data sources 115 include any third-party server or database.Third-party servers may host services such as email and instantmessaging services, banks and other financial institutions,social-networking websites, new sources, RSS feeds, and other websites.The remote data sources 115 can also include other devices similar tothe user device 105.

The environment 100 can optionally include the server 120. The server120 can store data associated with an instance of the intelligent userinterface system 130 residing on the user device 105. The server 120 canalso include the intelligent user interface system 130 to facilitategeneration of an intelligent user interface to be presented by the userdevice 105. In such a case, the user device 105 may access an instanceof the intelligent user interface system 130 being executed by theserver 120 via the network 110. Furthermore, the server 120 can executecertain components of the intelligent user interface system 130 locally,while other components are executed by the user device 105.

FIG. 2 is a block diagram of the exemplary intelligent user interfacesystem 130 that may be invoked in the environment 100 illustrated inFIG. 1. As illustrated in FIG. 2, the intelligent user interface system130 includes a knowledge base 205, a user data aggregation engine 210, asensory engine 215, a thought engine 220, an interaction engine 225, anda personality engine 230. The individual program components andapplications making up engines and modules of the intelligent userinterface system 130 may be stored in memory of devices such as the userdevice 105 or the server 120. The intelligent user interface system 130and its constituent engines and modules can be executed by a processorto effectuate respective functionalities attributed thereto. Theintelligent user interface system 130 may be composed of more or fewerengines/modules or combinations of the same and still fall within thescope of the present invention. For example, the functionalities of theinteraction engine 225 and the functionalities of the personality engine230 may be combined into a single engine or module.

The knowledge base 205 can be a database that is configured to storelearned idiosyncrasies and collected data of the user. Generally,learned idiosyncrasies are descriptive of individualizing qualities orcharacteristics of a particular user. The learned idiosyncrasies mayaccount for certain eccentricities or peculiarities by identified habitsand rituals of the user. Collected data of the user can encompass anyinformation associated with the user. For example, collected data caninclude various facts about the user such as who they are, where theycome from, and what they are interested in. The collected data may alsoinclude an index of user data stored locally or remotely such as gamedata, browser history, social network profile data, contacts, calendarevents, media files, and so forth. Such learned idiosyncrasies andcollected data may be regularly obtained by other constituent componentsof the intelligent user interface system 130 such that the knowledgebase 205 is kept up to date. The learned idiosyncrasies and collecteddata stored by the knowledge base 205 can be accessed by otherconstituent component of the intelligent user interface system 130.

The user data aggregation engine 210 is executable to update theknowledge base 205 with information associated with the user. Updatingthe knowledge base may include cataloging local data associated with auser such as locally stored media and calendar events. Collecting remotedata associated with the user such as memberships and purchaseinformation may also be part of updating the knowledge base 205. Theuser data aggregation engine 210 can also be executed to recordinformation associated with verbal input received from the user and totrack acts performed by the user to determine user idiosyncrasies.

The sensory engine 215 can be executed to obtain information from theuser environment 125 during learning of idiosyncrasies and/or collectionof data. Examples of such information include visual or audibleinformation. By being coupled to a microphone or array of microphonesand/image sensing device or camera, data concerning the user environment125 may be collected and processed by the sensory engine 215. Thisinformation could include the sound of a door opening at a particulartime of day, which would indicate a user arriving home whereby thesystem may then engage in the offering of thought-based statements(e.g., “welcome home”). Camera data such as an image of the user couldlikewise invoke a thought-based statement conversation particular to agiven user or conversation specific to a particular time of day based onlight levels (e.g., “good evening”). The position of a user in the roomor with respect to an input gathering device or in the real-world ingeneral may be gathered using GPS, triangulation, cellular base station,or other location based information. Location information may be derivedfrom other sources not traditionally associated with locationidentification but nevertheless indicative of the same (e.g., a debitcard charge at a restaurant having a particular restaurant). The sensoryengine 215 is described in further detail in connection with FIG. 2.

Execution of the thought engine 220 can generate thought-basedstatements based at least in part on the knowledge base 205 and theinformation from the user environment 125 obtained through execution ofthe sensory engine 215. The thought-based statements serve to invoke orrespond to subsequent actions of the user. An example of a thought-basedstatement might be “welcome home, would you like me to play some music”or “it is currently 6 PM, would you like me to suggest a restaurant fordinner?” The thought engine 220 is described in further detail inconnection with FIG. 4.

The interaction engine 225 is executable to present an intelligent userinterface and to allow for interaction with the user based at least inpart on the thought-based statements generated through execution of thethought engine 220. The intelligent user interface can include a numberof form factors. For example, the intelligent user interface may presenta visual image of face such that the interaction is akin to having aconversation with another real person. The interface could also be acharacter including a real-person (e.g., an avatar generated to appearsimilar to that of a person or randomly generated persona), a cartooncharacter (e.g., Homer Simpson), an animal (e.g., a talking dog) orother object (e.g, a blinking eye or giant lips). The interface couldalso be a touch screen, menu, or other data entry mechanism. Theinteraction engine 225 is described in further detail in connection withFIG. 5.

The personality engine 230 can be executed to develop personalitynuances of the intelligent user interface that affect the interactionbetween the user and the intelligent user interface. Such personalitynuances may include a particular sense of humor, inside knowledge of theuser, an inside joke, a particular tone, and facial expressions. Thepersonality engine 230 is described in further detail in connection withFIG. 8.

FIG. 3 is a block diagram of the exemplary sensory engine 215 that maybe included in the intelligent user interface system 130. As mentionedin connection with FIG. 2, the sensory engine 215 can be executed toobtain information from the user environment 125 during learning ofidiosyncrasies and/or collection of data. The sensory engine 215, asillustrated in FIG. 3, includes a speech module 305, a sight module 310,a sound module 315, and a position module 320. The individual programcomponents and applications making up modules of the sensory engine 215may be stored in memory of devices such as the user device 105 or theserver 120. The constituent modules of the sensory engine 215 can beexecuted by a processor to effectuate respective functionalitiesattributed thereto. The sensory engine 215 may be composed of more orfewer modules or combinations of the same and still fall within thescope of the present invention.

The speech module 305 can be executed to decipher detected speech fromthe user. The module 305 may utilize Hidden Markov Models (HMM). HMMoutput a sequence of symbols or quantities. The speech signal can beviewed as a piecewise stationary signal or a short-time stationarysignal whereby speech can be approximated as a stationary processallowing the speech to be thought of as a Markov model for stochasticprocesses. HMMs are popular in that they can be trained automaticallyand are simple and computationally feasible to use. The speech module305 may also use Viterbi algorithms, acoustic and language modelinformation, finite state transducers, and other speech recognitiontechniques.

The sight module 310 is executable to optically detect a body part ofthe user. For example, the sight module 310 can be executed to detect ahand of the user in order to detect a manual gesture. The sight module310 may also be executed to detect the face of the user such as toperform facial recognition.

In the latter example, a facial recognition algorithm may identify facesby extracting landmarks, or features, from an image of the subject'sface such as the relative position, size, and/or shape of the eyes,nose, cheekbones, and jaw. These features are then used to search forother images with matching features. Other algorithms normalize agallery of face images and then compress the face data, only saving thedata in the image that is useful for face detection; a probe image isthen compared with the face data. Recognition algorithms can generallybe divided into the geometric, which look at distinguishing features orphotometric, which is a statistical approach that distills an image intovalues and comparing the values with templates to eliminate variances.Other techniques include three-dimensional recognition that uses 3-Dsensors to capture information about the shape of a face to identifydistinctive features and skin texture analysis, which uses the visualdetails of the skin and turns the unique lines, patterns, and spots intoa mathematical space.

Optical information of the user environment 125 can be obtained using acamera communicatively coupled or integral with the user device 105, asdescribed in connection with FIG. 9.

Execution of the sound module 315 allows a response to an audio signalin the user environment 125 to be provided. Audio signals in the userenvironment 125 can be detected using a microphone integral orcommunicatively coupled with the user device 105, as described inconnection with FIG. 9. For example, the sound module 315 might identifya sudden sound against a previously existing background of silence asmight occur with the opening of a door in a previously empty room. Thatsound might indicate the presence of a user.

The position module 320 can be executed to determine the location and/ormotion of the user. Positional information indicative of the locationand motion of the user can be obtained through GPS and othertriangulation techniques, including base stations. For example, GPSinformation can be obtained using a GPS device communicatively coupledor integral with the user device 105, as described in connection withFIG. 9.

FIG. 4 is a block diagram of the exemplary thought engine 220 that maybe included in the intelligent user interface system 130. As mentionedin connection with FIG. 2, the thought engine can be executed togenerate thought-based statements based at least in part on theknowledge base 205 and the information from the user environment 125obtained through execution of the sensory engine 215. As illustrated inFIG. 4, the thought engine 220 includes an information evaluation module405, a thought formation module 410, and a thought prioritization module415. The individual program components and applications making upmodules of the thought engine 220 may be stored in memory of devicessuch as the user device 105 or the server 120. The constituent modulesof the thought engine 220 can be executed by a processor to effectuaterespective functionalities attributed thereto. The thought engine 220may be composed of more or fewer modules or combinations of the same andstill fall within the scope of the present invention.

The information evaluation module 405, when executed, evaluates all orsome portion of available information associated with the user. This canentail evaluation of the knowledge base 205 as well as the informationfrom the user environment 125 obtained though execution of the sensoryengine 215. Evaluation module 405 aggregates all available informationrelevant to a particular scenario to generate parameters that mightdrive a subsequent thought based statement generated by the thoughtformation module 410. Evaluation module 405 may access knowledge base205 to recognize certain patterns of behavior in light of currentsensory information. For example, if the knowledge base 205 reflectsthat a particular user arrives home Monday through Friday atapproximately 5:30 PM, the presence of sound corresponding to an openingdoor at 5.24 PM on a Thursday may similarly indicate the arrival of thatuser. With that information having been recognized by evaluation module405, the thought formation module 410 may then formulate an appropriatethought statement. Evaluation module 405 may similarly recognize thattwo users typically arrive home at the same time and require additionalinformation such as recognizing the voice of a user or processing imageinformation of the user. In this way, the thought formation module 410may then generate the appropriate greeting (e.g., “Hello, Will” or“Hello, Holly”).

The thought formation module 410 can be executed to formulate thethought-based statements in response to an evaluation of the knowledgebase 205 and the information from the user environment 125 as undertakenby evaluation module 405. The thought-formation module 410 may thenissue appropriate thought-based statements such as “Good evening, Will”when clock time indicates that it is 5:30 PM and Will typically arriveshome at 5:30, a camera having processed image data confirming that Willis, in fact, home rather than his roommate or girlfriend. Similarly, thethought formation module 410 may recognize, in light of parameters fromthe evaluation module 405, that any of those three persons might haveentered into the room and issue a more generic greeting such as “Goodevening, who has arrived home?” in order to prompt an informativeresponse from the user—that response also being processed by evaluationmodule 405.

The thought prioritization module 415 is executable to prioritize thethought-based statements based on importance. For example, theprioritization module 415 may indicate that of three thought-basedstatements identified as being appropriate for the arrival of a userinto the room at 5:30 PM on a Friday (as indicated by parametersgenerated by the evaluation module 405) that “Good evening, welcomehome” should be rendered before statements such as “would you like me tomake a dinner suggestion?” or “would you like me to play some music?” Ifthe entering user states, “thank you, I'm hungry, any suggestions fordinner” in response to the “welcome home greeting,” then theprioritization module may indicate that the next based statement shouldbe “would you like me to make a dinner suggestion?” rather thaninquiring as to music and launching a library of available music or eveninquiring into a particular song or artist. Prioritization is dependentupon the context of any given situation and history related to thatsituation as determined by the evaluation module 405.

FIG. 5 is a block diagram of the exemplary interaction engine 225 thatmay be included in the intelligent user interface system 130. Asmentioned in connection with FIG. 2, the interaction engine 225 can beexecuted to present an intelligent user interface and to allow forinteraction with the user based at least in part on the thought-basedstatements generated through execution of the thought engine 220. Theinteraction engine 225 depicted in FIG. 5 includes an action module 505,a reaction module 510, an interactive conversation module 515, and anoptional avatar module 520. The individual program components andapplications making up modules of the interaction engine 225 may bestored in memory of devices such as the user device 105 or the server120. The constituent modules of the interaction engine 225 can beexecuted by a processor to effectuate respective functionalitiesattributed thereto. The interaction engine 225 may be composed of moreor fewer modules or combinations of the same and still fall within thescope of the present invention.

The action module 505 is executable to perform actions based on thethought-based statements. For example, if a thought-based statementsuggests the playing of music, the action module 505 may launch a musiclibrary and indicate available songs and artists. Similarly, if astatement suggests restaurants, a map may be launched indicatinglocation, reviews, or means for making a reservation.

The reaction module 510 can be executed to perform reactions toinformation obtained from the user environment 125. If camera dataindicates that the light level in the room has dipped, the reactionmodule 510 can trigger the activation of room lighting if the system iscoupled to a light management system. Similarly, if sound volume dips inthe room, then the volume associated with music being played by thesystem will also dip to avoid it being too loud. In another example, ifthe phone rings (as indicated by the detected sound of a ringer orthrough a VOIP connection coupled to the system), the reaction module510 may pause playback of a movie or game and result in the generationof a thought based statement inquiring as to whether the call should beanswered.

The interactive conversation module 515 is executable to provide verbalresponses to verbal input by the user. For example, if a user requestsmusic, then the interactive conversation module 515 may respond, “I'd behappy to comply—is there a particular type of music you would like tolisten to?” By working in conjunction with other modules and theknowledge base 205, the interactive conversation module 515 maydetermine that a user likes a particular genre of music on particulardays or at particular times and suggest playback of that particulargenre in a similar situation.

Execution of the optional avatar module 520 allows presentation of anavatar to the user as a part of the intelligent user interface. FIG. 6is a collection of exemplary avatars that may be included in theintelligent user interface. Any number of the aforementioned modules mayinteract with other modules to provide a conversational, almost human,interactive experience.

FIG. 7 is a block diagram of the exemplary personality engine 230 thatmay be included in the intelligent user interface system 130. Asmentioned in connection with FIG. 2, the personality engine 230 can beexecuted to develop personality nuances of the intelligent userinterface that affect the interaction between the user and theintelligent user interface. As illustrated in FIG. 7, the personalityengine 230 includes a conversation analysis module 705, an experienceanalysis module 710, a goals module 715, and a desires module 720. Theindividual program components and applications making up modules of thepersonality engine 230 may be stored in memory of devices such as theuser device 105 or the server 120. The constituent modules of thepersonality engine 230 can be executed by a processor to effectuaterespective functionalities attributed thereto. The personality engine230 may be composed of more or fewer modules or combinations of the sameand still fall within the scope of the present invention.

The conversation analysis module 705 can be executed to analyze pastverbal input by the user. The generated thought-based statements may bebased in part the analysis of the past verbal input. For example,certain statements (“I had a lousy day”) may be indicative of mood orpresent feeling, which may be used to present certain options if similarconversational interactions are identified in the future.

The experience analysis module 710 is executable to analyze pastinteractions between the user and the user device 105. The generatedthought-based statements can be based in part on the analysis of thepast interactions. For example, a logic tree might be developed thatindicates a particular flow of conversation results in a particular setof discussion options (e.g., an inquiry as to food leads to offering upa suggestion, which then leads to type of food, followed by proximity,and ultimately the availability of reservations or take out).

Execution of the goals module 715 allows formation of goals of theintelligent user interface. The generated thought-based statements maybe based in part on the goals. The goals module 715 may, for example,work in conjunction with other modules to identify an ultimate result tobe generated from a conversation. For example, if a user inquires as todinner suggestions, the goals module 715 may recognize that itultimately needs to find a restaurant that is open, within drivingdistance (or some other parameter, which may in and of itself be agoal), of a particular type of food and have reservations for aparticular number of people at a particular time. AS a result ofrecognizing these goals, the requisite thought-based statements may begenerated as to generate the appropriate responsive answers. Whatconstitutes a goal for any given conversation may be recognized overtime from information gathered by the knowledge based 205.

The desires module 720 can be executed to form desires of theintelligent user interface. The generated thought-based statements canbe based in part on the desires. For example, if the system recognizesthat a user is in a bad mood, then desires module 720 may seek to arriveat some end result that cheers up the user. This may involve suggestinga particular activity, television show, or contacting a friend by phone.Like all modules of the present system, interaction with other modulesand data sources may be necessary to properly identify a state of mindor being of a user and that a particular desire or goal is appropriate.

FIG. 8 is a flowchart illustrating an exemplary method 800 for providingan intelligent user interface that evolves based on learnedidiosyncrasies and collected data of a user. The steps of the method 800may be performed in varying orders. Furthermore, steps may be added orsubtracted from the method 800 and still fall within the scope of thepresent technology. The methodology illustrated in FIG. 8 may beembodied on a computer-readable storage medium and executable by aprocessing device at any one of the devices illustrated in FIG. 1.

In step 805, learned idiosyncrasies and collected data of the user arestored in the knowledge base 205. Step 805 can be performed inconjunction with execution of the user data aggregation engine 210.

In step 810, information is obtained from the surrounding environment ofthe user (e.g., the user environment 125) during learning ofidiosyncrasies or collection of data. Step 810 can be performed by wayof execution of the sensory engine 215.

In step 815, thought-based statements are generated based at least inpart on the knowledge base 205 and the information from the environmentsurrounding the user during learning of idiosyncrasies or collection ofdata. As mentioned herein, the thought-based statements serve to invokeor respond to subsequent actions of the user. The thought engine 220 canbe executed to perform step 815.

In step 820, the user interface is presented and interaction with theuser is allowed therewith based at least in part on the thought-basedstatements. Step 820 can be performed through execution of theinteraction engine 225.

In step 825, personality nuances of the user interface are developedthat affect the interaction between the user and the user interface. Thepersonality engine 230 can be executed to perform step 825.

FIG. 9 is a block diagram illustrating an exemplary device 900 that maybe used to implement an embodiment of the present technology. The device900 may be implemented in the contexts of the likes of the user device105 and the server 120. The device 900 of FIG. 9 includes one or moreprocessors 910 and main memory 920. Main memory 920 stores, in part,instructions and data for execution by processor 910. Main memory 920can store the executable code when in operation. The device 900 of FIG.9 further includes a mass storage device 930, portable storage mediumdrive(s) 940, output devices 950, user input devices 960, a graphicsdisplay 970, and peripheral devices 980.

The components shown in FIG. 9 are depicted as being connected via asingle bus 990. The components may be connected through one or more datatransport means. The processor unit 910 and the main memory 920 may beconnected via a local microprocessor bus, and the mass storage device930, peripheral device(s) 980, portable storage device 940, and displaysystem 970 may be connected via one or more input/output (I/O) buses.

Mass storage device 930, which may be implemented with a magnetic diskdrive or an optical disk drive, is a non-volatile storage device forstoring data and instructions for use by processor unit 910. Massstorage device 930 can store the system software for implementingembodiments of the present invention for purposes of loading thatsoftware into main memory 920.

Portable storage device 940 operates in conjunction with a portablenon-volatile storage medium, such as a floppy disk, compact disk,digital video disc, or USB storage device, to input and output data andcode to and from the device 900 of FIG. 9. The system software forimplementing embodiments of the present invention may be stored on sucha portable medium and input to the device 900 via the portable storagedevice 940.

Input devices 960 provide a portion of a user interface. Input devices960 may include an alpha-numeric keypad, such as a keyboard, forinputting alpha-numeric and other information, or a pointing device,such as a mouse, a trackball, stylus, or cursor direction keys.Additionally, the device 900 as shown in FIG. 9 includes output devices950. Suitable output devices include speakers, printers, networkinterfaces, and monitors.

Display system 970 may include a liquid crystal display (LCD) or othersuitable display device. Display system 970 receives textual andgraphical information, and processes the information for output to thedisplay device.

Peripherals 980 may include any type of computer support device to addadditional functionality to the computer system. Peripheral device(s)980 may include a modem, a router, a camera, a microphone, and a GPSreceiver. Peripheral device(s) 980 can be integral or communicativelycoupled with the device 900.

The components contained in the device 900 of FIG. 9 are those typicallyfound in computing systems that may be suitable for use with embodimentsof the present invention and are intended to represent a broad categoryof such computing components that are well known in the art. Thus, thedevice 900 of FIG. 9 can be a home entertainment system, personalcomputer, hand-held computing device, telephone, mobile computingdevice, workstation, server, minicomputer, mainframe computer, or anyother computing device. The device 900 can also include different busconfigurations, networked platforms, multi-processor platforms, etc.Various operating systems can be used including Unix, Linux, Windows,Macintosh OS, Palm OS, webOS, Android, iPhone OS, and other suitableoperating systems.

It is noteworthy that any hardware platform suitable for performing theprocessing described herein is suitable for use with the technology.Computer-readable storage media refer to any medium or media thatparticipate in providing instructions to a central processing unit(CPU), a processor, a microcontroller, or the like. Such media can takeforms including, but not limited to, non-volatile and volatile mediasuch as optical or magnetic disks and dynamic memory, respectively.Common forms of computer-readable storage media include a floppy disk, aflexible disk, a hard disk, magnetic tape, any other magnetic storagemedium, a CD-ROM disk, digital video disk (DVD), any other opticalstorage medium, RAM, PROM, EPROM, a FLASHEPROM, any other memory chip orcartridge.

While various embodiments have been described above, it should beunderstood that they have been presented by way of example only, and notlimitation. The descriptions are not intended to limit the scope of thetechnology to the particular forms set forth herein. Thus, the breadthand scope of a preferred embodiment should not be limited by any of theabove-described exemplary embodiments. It should be understood that theabove description is illustrative and not restrictive. To the contrary,the present descriptions are intended to cover such alternatives,modifications, and equivalents as may be included within the spirit andscope of the technology as defined by the appended claims and otherwiseappreciated by one of ordinary skill in the art. The scope of thetechnology should, therefore, be determined not with reference to theabove description, but instead should be determined with reference tothe appended claims along with their full scope of equivalents.

What is claimed is:
 1. A method for providing a user interface thatevolves based on learned idiosyncrasies and collected data of a user,the method comprising: storing learned idiosyncrasies and collected dataof the user in a knowledge base; executing instructions stored in memoryto obtain information from the surrounding environment of the userduring learning of idiosyncrasies or collection of data; executinginstructions stored in memory to generate thought-based statements basedat least in part on the knowledge base and the information from theenvironment surrounding the user during learning of idiosyncrasies orcollection of data, the thought-based statements serving to invoke orrespond to subsequent actions of the user; executing instructions storedin memory to present the user interface and to allow for interactionwith the user based at least in part on the thought-based statements;and executing instructions stored in memory to develop personalitynuances of the user interface that affect the interaction between theuser and the user interface, wherein executing instructions to developthe personality nuances includes analyzing past verbal input by theuser, wherein the generated thought-based statements are further basedon the analysis of the past verbal input.
 2. The method of claim 1,wherein executing instructions to obtain the information from thesurrounding environments includes deciphering detected speech from theuser.
 3. The method of claim 1, wherein executing instructions to obtainthe information from the surrounding environments includes opticallydetecting a body part of the user.
 4. The method of claim 3, whereinoptically detecting the body part includes detecting a manual gesture.5. The method of claim 3, wherein optically detecting the body partincludes performing facial recognition.
 6. The method of claim 1,wherein executing instructions to obtain the information from thesurrounding environment includes determining one or more of the locationof the user or motion of the user.
 7. The method of claim 1, whereinexecuting instructions to obtain the information from the surroundingenvironments includes providing a response to an audio signal in thesurrounding environment of the system.
 8. The method of claim 1, whereinexecuting instructions to generate the thought-based statements includesprioritizing the thought-based statements based on importance.
 9. Themethod of claim 1, wherein the user interface includes an avatar. 10.The method of claim 1, wherein executing instructions to develop thepersonality nuances includes analyzing past interactions between theuser and the system, wherein the generated thought-based statements arefurther based on the analysis of the past interactions.
 11. The methodof claim 1, wherein executing instructions to develop the personalitynuances includes forming desires of the intelligent user interface,wherein the generated thought-based statements are further based on thedesires.
 12. The method of claim 1, wherein executing instructions todevelop the personality nuances includes forming goals of theintelligent user interface, wherein the generated thought-basedstatements are further based on the goals.
 13. A method for providing auser interface that evolves based on learned idiosyncrasies andcollected data of a user, the method comprising: storing learnedidiosyncrasies and collected data of the user in a knowledge base;executing instructions stored in memory to obtain information from thesurrounding environment of the user during learning of idiosyncrasies orcollection of data; executing instructions stored in memory to generatethought-based statements based at least in part on the knowledge baseand the information from the environment surrounding the user duringlearning of idiosyncrasies or collection of data, the thought-basedstatements serving to invoke or respond to subsequent actions of theuser; executing instructions stored in memory to present the userinterface and to allow for interaction with the user based at least inpart on the thought-based statements; and executing instructions storedin memory to develop personality nuances of the user interface thataffect the interaction between the user and the user interface, whereinexecuting instructions to develop the personality nuances includesanalyzing past interactions between the user and the system, wherein thegenerated thought-based statements are further based on the analysis ofthe past interactions.
 14. The method of claim 13, wherein executinginstructions to obtain the information from the surrounding environmentsincludes deciphering detected speech from the user.
 15. The method ofclaim 13, wherein executing instructions to obtain the information fromthe surrounding environments includes optically detecting a body part ofthe user.
 16. The method of claim 15, wherein optically detecting thebody part includes detecting a manual gesture.
 17. The method of claim15, wherein optically detecting the body part includes performing facialrecognition.
 18. The method of claim 13, wherein executing instructionsto obtain the information from the surrounding environment includesdetermining one or more of the location of the user or motion of theuser.
 19. The method of claim 13, wherein executing instructions toobtain the information from the surrounding environments includesproviding a response to an audio signal in the surrounding environmentof the system.
 20. The method of claim 13, wherein executinginstructions to generate the thought-based statements includesprioritizing the thought-based statements based on importance.
 21. Themethod of claim 13, wherein the user interface includes an avatar.
 22. Amethod for providing a user interface that evolves based on learnedidiosyncrasies and collected data of a user, the method comprising:storing learned idiosyncrasies and collected data of the user in aknowledge base; executing instructions stored in memory to obtaininformation from the surrounding environment of the user during learningof idiosyncrasies or collection of data; executing instructions storedin memory to generate thought-based statements based at least in part onthe knowledge base and the information from the environment surroundingthe user during learning of idiosyncrasies or collection of data, thethought-based statements serving to invoke or respond to subsequentactions of the user; executing instructions stored in memory to presentthe user interface and to allow for interaction with the user based atleast in part on the thought-based statements; and executinginstructions stored in memory to develop personality nuances of the userinterface that affect the interaction between the user and the userinterface, wherein executing instructions to develop the personalitynuances includes forming desires of the intelligent user interface,wherein the generated thought-based statements are further based on thedesires.
 23. The method of claim 22, wherein executing instructions toobtain the information from the surrounding environments includesdeciphering detected speech from the user.
 24. The method of claim 22,wherein executing instructions to obtain the information from thesurrounding environments includes optically detecting a body part of theuser.
 25. The method of claim 24, wherein optically detecting the bodypart includes detecting a manual gesture.
 26. The method of claim 24,wherein optically detecting the body part includes performing facialrecognition.
 27. The method of claim 22, wherein executing instructionsto obtain the information from the surrounding environment includesdetermining one or more of the location of the user or motion of theuser.
 28. The method of claim 22, wherein executing instructions toobtain the information from the surrounding environments includesproviding a response to an audio signal in the surrounding environmentof the system.
 29. The method of claim 22, wherein executinginstructions to generate the thought-based statements includesprioritizing the thought-based statements based on importance.
 30. Themethod of claim 22, wherein the user interface includes an avatar.
 31. Amethod for providing a user interface that evolves based on learnedidiosyncrasies and collected data of a user, the method comprising:storing learned idiosyncrasies and collected data of the user in aknowledge base; executing instructions stored in memory to obtaininformation from the surrounding environment of the user during learningof idiosyncrasies or collection of data; executing instructions storedin memory to generate thought-based statements based at least in part onthe knowledge base and the information from the environment surroundingthe user during learning of idiosyncrasies or collection of data, thethought-based statements serving to invoke or respond to subsequentactions of the user; executing instructions stored in memory to presentthe user interface and to allow for interaction with the user based atleast in part on the thought-based statements; and executinginstructions stored in memory to develop personality nuances of the userinterface that affect the interaction between the user and the userinterface, wherein executing instructions to develop the personalitynuances includes forming goals of the intelligent user interface,wherein the generated thought-based statements are further based on thegoals.
 32. The method of claim 31, wherein executing instructions toobtain the information from the surrounding environments includesdeciphering detected speech from the user.
 33. The method of claim 31,wherein executing instructions to obtain the information from thesurrounding environments includes optically detecting a body part of theuser.
 34. The method of claim 33, wherein optically detecting the bodypart includes detecting a manual gesture.
 35. The method of claim 33,wherein optically detecting the body part includes performing facialrecognition.
 36. The method of claim 31, wherein executing instructionsto obtain the information from the surrounding environment includesdetermining one or more of the location of the user or motion of theuser.
 37. The method of claim 31, wherein executing instructions toobtain the information from the surrounding environments includesproviding a response to an audio signal in the surrounding environmentof the system.
 38. The method of claim 31, wherein executinginstructions to generate the thought-based statements includesprioritizing the thought-based statements based on importance.
 39. Themethod of claim 31, wherein the user interface includes an avatar.